Index of modules


B
Block_diag
Type of block diagonal matrices

C
Co_variance_predictor [Interfaces.Sigs.Eval]
Module for making (co-)variance predictions
Cov_const
Covariance of a constant function
Cov_lin_ard
Covariance of linear functions with Automatic Relevance Determination
Cov_lin_one
Covariance of linear functions with one hyperparameter
Cov_sampler [Interfaces.Sigs.Eval]
Module for sampling (multiple) points from the posterior distribution accounting for their covariance
Cov_se_fat
Feature-rich ("fat") squared exponential covariance
Cov_se_iso
Isotropic squared exponential covariance
Covariances [Interfaces.Sigs.Eval]
Posterior covariances

D
Deriv [Cov_se_fat]
Deriv [Cov_se_iso]
Deriv [Cov_lin_one]
Deriv [Cov_lin_ard]
Deriv [Cov_const]
Deriv [Interfaces.Sigs.Deriv]
Sub-modules for learning with derivatives.
Dim_hyper [Cov_se_fat]

E
Eval [Cov_se_fat]
Eval [Cov_se_iso]
Eval [Cov_lin_one]
Eval [Cov_lin_ard]
Eval [Cov_const]
Eval [Interfaces.Sigs.Optimizer]
Sub-modules for learning without derivatives.
Eval [Interfaces.Sigs.Deriv]
Sub-modules for learning without derivatives.
Eval [Interfaces.Specs.Optimizer]
Derivatives always require evaluation functions
Eval [Interfaces.Specs.Deriv]
Derivatives always require evaluation functions

F
FIC [Fitc_gp.Make_deriv]
FIC [Fitc_gp.Make]
FITC [Fitc_gp.Make_deriv]
FITC [Fitc_gp.Make]
Fitc_gp
Evaluation

G
Gpr_utils
Gsl [Interfaces.Sigs.Deriv.Deriv.Optim]
Optimization with the GNU Scientific library (GSL)

H
Hyper [Interfaces.Specs.Deriv]
Hyper parameters that have derivatives
Hyper_repr [Cov_se_fat]

I
Inducing [Interfaces.Sigs.Deriv.Deriv]
Module for inducing inputs with derivatives
Inducing [Interfaces.Sigs.Eval]
Evaluating inducing inputs
Inducing [Interfaces.Specs.Deriv]
Derivatives of the covariance matrix of inducing inputs
Inducing [Interfaces.Specs.Eval]
Signature for evaluating inducing inputs
Inducing_hyper [Cov_se_fat]
Input [Interfaces.Sigs.Eval]
Evaluating single inputs
Input [Interfaces.Specs.Optimizer]
Input [Interfaces.Specs.Eval]
Signature for evaluating single inputs
Inputs [Interfaces.Sigs.Deriv.Deriv]
Module for inputs with derivatives
Inputs [Interfaces.Sigs.Eval]
Evaluating (multiple) inputs
Inputs [Interfaces.Specs.Optimizer]
Inputs [Interfaces.Specs.Deriv]
Derivatives of the (cross-) covariance matrix of inputs.
Inputs [Interfaces.Specs.Eval]
Signature for evaluating multiple inputs
Int_vec [Gpr_utils]
Interfaces
Representations of (sparse) derivative matrices

K
Kernel [Interfaces.Specs.Eval]
Kernel used for evaluation

M
Make [Fitc_gp]
Make_FIC [Fitc_gp]
Make_FIC_deriv [Fitc_gp]
Make_FITC [Fitc_gp]
Make_FITC_deriv [Fitc_gp]
Make_deriv [Fitc_gp]
Make_variational_FIC [Fitc_gp]
Make_variational_FIC_deriv [Fitc_gp]
Make_variational_FITC [Fitc_gp]
Make_variational_FITC_deriv [Fitc_gp]
Mean [Interfaces.Sigs.Eval]
Posterior mean for a single input
Mean_predictor [Interfaces.Sigs.Eval]
Module for making mean predictions
Means [Interfaces.Sigs.Eval]
Posterior means for (multiple) inputs
Model [Interfaces.Sigs.Deriv.Deriv]
(Untrained) model with derivative information
Model [Interfaces.Sigs.Eval]
(Untrained) model - does not require targets

O
Optim [Interfaces.Sigs.Deriv.Deriv]
Optimization module for evidence maximization
Optimizer [Interfaces.Sigs.Optimizer]
Sub-modules for global optimization.

P
Params [Cov_se_fat]
Params [Cov_se_iso]
Params [Cov_lin_one]
Params [Cov_lin_ard]
Params [Cov_const]
Proj_hyper [Cov_se_fat]

S
SGD [Interfaces.Sigs.Deriv.Deriv.Optim]
SMD [Interfaces.Sigs.Deriv.Deriv.Optim]
Sampler [Interfaces.Sigs.Eval]
Module for sampling single points from the posterior distribution
Sigs [Interfaces]
Signatures for learning sparse Gaussian processes with inducing inputs
Sparse_indices [Interfaces]
Representation of indices into sparse matrices
Spec [Interfaces.Sigs.Optimizer.Optimizer]
Spec [Interfaces.Sigs.Deriv.Deriv]
Specification of covariance function derivatives
Spec [Interfaces.Sigs.Eval]
Specification of covariance function
Specs [Interfaces]
Specifications of covariance functions (= kernels) and their derivatives
Stats [Interfaces.Sigs.Eval]
Statistics derived from trained models

T
Test [Interfaces.Sigs.Deriv.Deriv]
Module for testing derivative code
Trained [Interfaces.Sigs.Deriv.Deriv]
Trained model with derivative information
Trained [Interfaces.Sigs.Eval]
Trained model - requires targets

V
Var [Interfaces.Specs.Optimizer]
Input parameters that have derivatives
Variance [Interfaces.Sigs.Eval]
Posterior variance for a single input
Variances [Interfaces.Sigs.Eval]
Posterior variances for (multiple) inputs
Variational_FIC [Fitc_gp.Make_deriv]
Variational_FIC [Fitc_gp.Make]
Variational_FITC [Fitc_gp.Make_deriv]
Variational_FITC [Fitc_gp.Make]
Version